The present invention relates to an image compressing method and an image compressing apparatus which are used for image compression or the like operation.
In techniques for high-efficiency coding of images presupposing communication media or recording media, a technique using DCT (discrete cosine conversion) has been gaining widespread applications. A technique for compression using the DCT, however, faces essential problems that with the compression ratio increased, block distortion, mosquito noise and the like are visually recognized and the compression ratio is limited.
Accordingly, new compressing methods have recently been proposed for the purpose of improving the compression ratio and especially, a compressing technique using wavelet conversion which is one of subband coding modes has been highlighted. By using the wavelet conversion, block distortion which would otherwise take place in the DCT can be eliminated because the concept of block is not involved in the wavelet conversion and image quality can be visually improved to a great extent.
Of the DCT and the wavelet technique, the DCT dealing with digital images can advantageously conserve high-frequency components by increasing the compression ratio but conversely, visually prominent distortion constructed of high-frequency components takes place. On the other hand, in the case of the wavelet technique dealing with analog images, high-frequency components are spontaneously dropped off as the compression ratio increases. In other words, the signal band is gradually cut starting with a high-frequency portion. As a result, the resolution decreases as a whole and visual image quality is less degraded for the same compression ratio in the wavelet technique than in the DCT.
A conventional wavelet image compressing apparatus will now be described with reference to FIG. 13. Firstly, in the compressing processing of moving image data, input image data is fed to a frame memory 101. Subsequently, output data from the frame memory 101 is fed to a wavelet converter 102. The wavelet conversion will be described below in greater detail.
FIG. 14 is a block diagram showing the operation processing of the wavelet conversion. As shown in FIG. 14, an input image data is inputted to a horizontal low-pass filter (LPF) and a horizontal high-pass filter (HPF) in order that the band in the horizontal direction is divided into halves and the data amount in each half is thinned out by down sampling to a half by means of a 1/2 subsampler (downward arrow). The input image data whose data amount has been thinned out to the half through the horizontal low-pass filter (LPF) is inputted to a vertical low-pass filter (LPF) and a vertical high-pass filter (HPF) in order that the band in the vertical direction is divided into halves and the data amount in each half is thinned out by down sampling to a half by means of a 1/2 subsampler (downward arrow).
It is now assumed that an input image data component which is passed through the horizontal low-pass filter (LPF), thinned out to the halved data amount, passed through the subsequent vertical high-pass filter (HPF) and thinned out to the halved data amount results in image data designated by W1LH, that an input image data component which is passed through the horizontal high-pass filter (HPF), thinned out to the halved data amount, passed through the subsequent vertical low-pass filter (LPF) and thinned out to the halved data amount results in image data designated by W1HL, and that an input image data component which is passed through the horizontal high-pass filter (HPF), thinned out to the halved data amount, passed through the subsequent vertical high-pass filter (HPF) and thinned out to the halved data amount results in image data designated by W1HH.
A component which is passed through the aforementioned horizontal low-pass filter (LPF), thinned out to the halved data amount, passed through the subsequent vertical low-pass filter (LPF) and thinned out by down sampling to the halved data amount is again subjected to the above processing. Through the repetition of the processing, coefficient data pieces can eventually be obtained by dividing the frequency in the horizontal and vertical directions along the lower-frequency region and decreasing the data amount to a half and these coefficient data pieces are cumulated. Wavelet conversion coefficient signals in a plurality of frequency bands are shown in a diagram of FIG. 15.
For convenience of explanation, a state of the wavelet conversion effected up to the third operation is shown in FIG. 14. Thus, the coefficient data pieces subject to the wavelet conversion are distributed in the horizontal and vertical directions to form a hierarchical structure.
Returning to FIG. 13, coefficients associated with the respective frequency bands obtained through the conversion by the wavelet converter 102 having the above characteristics are quantized by a quantizing unit 103 and data pieces delivered out of the quantizing unit 103 are coded by a variable length coding unit 104 in such a manner that a greater amount of information is allotted to a data piece, of data pieces delivered out of the quantizing unit 103, which occurs at a higher probability. In this manner, the compression processing of the input image can be carried out while the information amount of the entire data being decreased.
In the expansion processing, a conversion mode can be carried out in which images in the four W3 regions are decoded to W1 images in FIG. 15 to superimpose the higher-frequency component on the lower-frequency component, thereby improving the resolution stepwise.
In the conventional construction, however, the coefficient of the higher-frequency subband is coded in an ordinary manner for not only a portion at which the coefficient of the lower-frequency subband is "0" but also a portion at which it is not "0".